Professor Perla Balbuena will develop molecular modeling methods to study the crystalline and interfacial structure and properties of metals, carbon-metal, alloys and electrolytes. The properties of particular interest are ionic diffusion coefficients, ionic conductivities, solvation structures, heats of adsorption and reaction. The outcome will impact chemical and electrochemical principles and applications. It will pertain mostly to industrial products such as adsorbents, catalysts, batteries, and fuel cells; the fundamental physicochemical phenomena involved in their utilization; and the applied processes derived from them. The first objective of the research is the modeling of Li intercalation in graphite. The expected result is prediction and validation of the dependence of open-circuit voltage and differential capacity with respect to composition, and the conditions for the transition from the super dense phase LiC2 to LiC6. The second objective is the determination of diffusion dynamics of Li and perchlorate ions, and of ion-pair association of Li perchlorate, in ethylene carbonate and propylene carbonate electrolytes. Following that objective, the PI will investigate the mechanism of degradation of graphite electrodes, in particular the formation of a presumed Li2CO3 passivation layer. She will also model the intercalation of solvated species into graphite. The third objective is the study of methane cracking over Ni and Ni/Cu to produce hydrogen and carbon, and the related phenomenon of hydrogen storage in carbon. These investigations will involve the development of structural models, ab initio and semiempirical quantum mechanical calculations, and molecular dynamics simulations, for chemical and electrochemical systems of practical importance. The methodology to be developed will likely have impact in the training of chemical engineering students as well as the practice of process and product design. The PI is developing new introductory courses and modifying the existing ones to raise the engineering students' capability to predict microscopic properties from first principles.